1. Field of the Invention
This invention relates to a fuzzy inference system for processing fuzzy conception found in pattern information or data, and a pattern input type membership value generator employed in the fuzzy inference system.
2. Discussion of the Related Art
Fuzzy technology is a technology for processing vagueness. A data process executed by men is performed by using vague language, and many human knowledge are expressed by using such vague language.
Knowledge (rules) expressed by such vague language is classified by the following various levels:
(1) IF water draw is "little", the season is "spring" and the time is "morning", THEN the pouring ratio is slightly enlarged. PA1 (2) IF a pictured image is "sport car", its color is "reddish", and its speed is "high", THEN alarm is set to a medium degree. PA1 (3) IF a pictured image is "stiff" and its pattern is "quiet", THEN purchase desire is decreased. PA1 (4) IF a company management is "innovative" and its atmosphere is "cheerful", THEN popularity by students increases. PA1 (5) IF our working is "good", THEN society is improved.
Most of conventional fuzzy technologies allow fuzzy inference or fuzzy control by employing membership values (degrees of adaptation) generated from membership functions entered by scalar quantity signals. In the above-mentioned knowledge, for example, "little" of the item (1) and "high" of the item (2) are scalar quantity. "spring" and "morning" in the knowledge of the items (1) and (2) may be converted to scalar quantity. The conventional fuzzy technologies can process only the knowledge at the level of the item (1). Processable data are limited to data in which a scalar type of physical quantity is defined as a trapezoidal set and a membership function can be defined in the trapezoidal set.
Fuzzy conception such as sport car in the knowledge of the above item (2) cannot be expressed by any membership function based on a trapezoidal set of a single scalar type of physical quantity, nor by any framework of membership function. The pattern conception of "sport car" cannot be expressed by other framework than the framework of at least entering a picture image given by television camera. Generally speaking, the knowledge of the above item (2) requires a framework for processing a fuzzy conception corresponding to pattern data.
The knowledge of the above item (3) also requires a framework for processing a fuzzy conception corresponding to pattern data, like the knowledge of the item (2). Though in the item (2) physical pattern data is directly processed, in he item (3) a pattern obtained by reproducing an image of physical patter data in other space is processed. The knowledge of the items (4) and (5) are scalar type of physical quantity, but do not correspond to any physical pattern data. In fact, kinds of the data to be corresponded cannot be known. Conveniently it is possible to make various operating index or a value of results of questionnaire correspond to the knowledge of the above item (4) or (5). It is, however, apparent to do not catch any substance of the knowledge of the item (4) or (5).
Thus, according to conventional fuzzy technologies, only scalar type of physical quantity can be processed, whereby only very simple knowledge can be expressed. Accordingly, conventional fuzzy technology has the disadvantage that complicated data process for supporting decision making or estimate by men is difficult.